Chat GPT Prompt Engineering With Tech Trends: Tech trends, #1

1.1 AI-Assisted Programming

As we step into the future of software development, AI-assisted programming has become a game-changer. Chances are, you have already come across conversations or demonstrations about using tools like ChatGPT for programming. By providing a simple prompt, AI generates fully written code that can be easily integrated into your project. In this sub-chapter, we will discuss the concept of AI as a programming partner, its capabilities, inner workings, and what to expect in the near future.

There are numerous AI-assisted programming tools available, but we will focus on three key players: ChatGPT, Microsoft Bing, and GitHub Copilot. These tools offer a solid framework for understanding the technology and represent the variety of tools on the market.

AI-assisted programming tools are generative in nature, meaning they can create code based on prompts. Beyond code generation, they can also detect errors, explain code functionality, add comments, reformat code, translate languages, and even write tests. Specialised tools like GitHub Copilot can even anticipate your thoughts, acting as a highly intelligent auto-complete feature.

These AI tools enable developers to write code more efficiently and quickly, saving time by offering ready-to-use examples, patterns, and prototypes. The secret behind AI's ability to write code lies in the fact that code is just another form of language. Large language models like ChatGPT are trained using coding languages, allowing them to generate code-like sentences based on their training data.

However, it's crucial to understand that there is no conscious, intelligent agent within these systems actively writing code. Instead, generative AI interprets prompts and constructs sentences by statistically guessing the next word. Because coding languages are more structured and patterned than human languages, AI-generated code is often functional.

AI programming tools have different approaches and strengths. ChatGPT is a general-purpose model that can interact with data, while Bing uses ChatGPT as an interface between users and the internet. On the other hand, GitHub Copilot is a specialised AI programming tool embedded within code editors.

1.1.1 ChatGPT

ChatGPT, developed by OpenAI, is a generative pre-trained transformer language model. It has received attention for its ability to generate human-like text based on provided prompts. While it's mainly designed to interact with data, it can also generate code-like sentences

when given the right input. However, it's limited by the knowledge in its training data, which was last updated in September 2021. To learn more about ChatGPT, visit the OpenAI website:

•  OpenAI's ChatGPT: https://platform.openai.com/docs/guides/chat

1.1.2 Microsoft Bing

Microsoft Bing is a search engine that integrates AI-powered features like ChatGPT to provide an improved user experience. When given a prompt, Bing searches the internet for relevant information and then generates responses that include links to authoritative sources. This allows users to verify the information provided and explore further if needed. To learn more about Microsoft Bing and its AI capabilities, visit the following resources:

•  Microsoft Bing: https://www.bing.com/

•  Microsoft AI: https://www.microsoft.com/en-us/ai

1.1.3 GitHub Copilot

GitHub Copilot is a specialised AI-assisted programming tool developed by GitHub and OpenAI. It works as an AI-powered code completion tool, providing developers with code suggestions based on their input. Copilot is designed to adapt to a developer's coding style and can generate code for various programming languages and frameworks. The official GitHub Copilot website offers more information and a preview of its features:

•  GitHub Copilot: https://copilot.github.com/

By leveraging these AI tools, developers can write code more efficiently and quickly. They save time by offering ready-to-use examples, patterns, and prototypes. AI's ability to write code lies in the fact that code is just another form of language. Large language models like ChatGPT are trained using coding languages, allowing them to generate code-like sentences based on their training data.

To make the most of AI-assisted programming tools, it is essential to:

Integrate them into your workflow. Screenshot 2023-04-11 at 15.58.17.png

Source information from reliable AI tools.

Maintain a solid understanding of modern coding standards and best practices.

To stay updated with the latest advancements in AI-assisted programming, consider following the official blogs and news sections of OpenAI, Microsoft, and GitHub:

•  OpenAI Blog: https://openai.com/blog/

•  Microsoft AI Blog: https://blogs.microsoft.com/ai/

•  GitHub Blog: https://github.blog/

By exploring these resources and integrating AI-assisted programming into your work, you will be better equipped to navigate the ever-evolving landscape of software development.

In conclusion, AI programming tools are valuable resources for developers and are continually improving. While they are not yet advanced enough to replace human programmers, they save significant time in code writing and research. To make the most of these tools, it is essential to integrate them into your workflow, source information from reliable AI tools, and maintain a solid understanding of modern coding standards and best practices. Embrace AI-assisted programming today and enhance your coding experience.

1.2 Generative Pre-trained Transformers (GPT-4)

1.2.1 Introduction to GPT-4

Generative Pre-trained Transformers (GPT) are a series of increasingly powerful AI language models developed by OpenAI. The most recent release, GPT-4, is a significant advancement in the GPT series, offering improved reasoning, concise answers, and several new capabilities. In this section, we will explore the differences between GPT-3 and GPT-4, the new features introduced in GPT-4, and its applications in various industries.

1.2.2 Understanding GPT

GPT stands for Generative Pre-trained Transformer. It is a neural network that generates content, such as stories or art, using massive amounts of data. As a transformer, it identifies keywords from human input and infers intent to provide contextually relevant responses. However, without specific details, it makes assumptions based on the most likely correct answer for a given situation.

1.2.3 GPT-3 vs. GPT-4

GPT-4 is a significant improvement over its predecessor, GPT-3. While GPT-4 is slower and requires more computational power, it offers better reasoning and more concise answers. OpenAI has fine-tuned GPT-4 to reduce hallucinations, biases, and improve overall safety.

GPT-4 is integrated into OpenAI's ChatGPT Plus subscription, Microsoft's Bing, Microsoft 365, and Azure. Its performance on tasks such as passing the bar exam, a test for lawyers, has improved significantly, moving from the lower 10th percentile in GPT-3 to the top 10th percentile in GPT-4.

1.2.4 GPT-4's Enhanced Capabilities

GPT-4 has several new features that set it apart from its predecessor:

•  Expanded input size: GPT-4 can accept up to 25,000 words of text, enabling it to process longer inputs and provide more detailed outputs.

•  Improved steerability: Users can control GPT-4's personality, verbosity, and style more effectively. For instance, they can request a Socratic mode where GPT-4 guides users to answers through leading questions.

•  Image and graphic understanding: GPT-4 can interpret photos and graphics, opening up possibilities for new applications, such as providing recipes based on fridge contents or interpreting data from charts and graphs.

1.2.5 Applications and Integrations